Job Details
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Job Description
Weekly Hours: 40
Role Number: 200646328-0836
Summary
Imagine what you could do here. The people here at Apple don't just create products - they create the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it.
Data Solutions & Initiatives (DSI) is a dynamic team within Apple’s Worldwide Sales organization. Our mission is to drive innovation through product design, engineering, and portfolio management. We thrive in a startup-like atmosphere where individuals take ownership and have a significant impact on the final product. In this environment, we move quickly, experiment boldly, and expect our team to take full ownership of what they deliver.
Description
We are looking for a Senior Engineer to help us transition from centralized data management to a scalable, self-service data mesh. In this role, you won't just move data, you will build the software and services that make data discoverable, reliable, and "product-ready" for the entire organization.
As an engineer focused on data platform, you will operate at the intersection of backend engineering and data engineering. You will design and own data products delivered through software, including curated datasets, data services, and APIs that power analytics, applications and AI/ML use cases. This includes building batch and real-time streaming pipelines, backend services, and developer-facing tools.
You’ll drive architecture, system design, and engineering standards while working closely with data, platform, and product teams. While a DevOps team supports infrastructure, you will be hands-on with cloud-native systems and own services end to end.
Minimum Qualifications
7+ years of experience in software/data engineering, with focus on data architecture
Strong programming skills in Python and/or Java/Scala/Go
Proficiency in data modeling, SQL, partitioning strategies, and query optimization
Hands-on experience with modern data stack (e.g., Flink, Kafka, dbt, Airflow, Spark, Iceberg or similar)
Experience with Open Table Formats (e.g., Apache Iceberg, Delta Lake) and catalog management
Solid experience building APIs, services, and distributed systems
Proven track record of implementing CI/CD, automated testing, data quality validation, and observability (logging, metrics, tracing) for data systems
Experience with cloud and containerized systems (e.g., AWS/GCP, Kubernetes, Docker)
Preferred Qualifications
Experience building internal data platforms or developer-facing tools
Solid experience with data mesh and “Data as a Product” principles
Experience building the data foundations for GenAI or ML workflows
Knowledge of data governance, lineage, and metadata systems
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